CN102175256A - Path planning determining method based on cladogram topological road network construction - Google Patents

Path planning determining method based on cladogram topological road network construction Download PDF

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CN102175256A
CN102175256A CN 201010606776 CN201010606776A CN102175256A CN 102175256 A CN102175256 A CN 102175256A CN 201010606776 CN201010606776 CN 201010606776 CN 201010606776 A CN201010606776 A CN 201010606776A CN 102175256 A CN102175256 A CN 102175256A
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node
road network
tree
chadogram
full
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CN102175256B (en
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张贵军
吴海涛
郭海峰
洪榛
何洋军
金媚媚
俞立
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Zhejiang University of Technology ZJUT
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Abstract

The invention discloses a path planning determining method based on cladogram topological road network construction, which comprises the steps of: obtaining city complete road network data, constructing a road network full-connected graph G expressing original geographic information by applying an adjacent topological cladogram; classifying and dividing the road network full-connected graph G into a Y-type road network topological cladogram; obtaining the minimal branching tree comprising all target nodes; and eliminating invalid branching nodes by adopting a branching delimiting searching strategy for the minimal branching tree comprising all target nodes in a road planning problem, reducing incidence matrix dimensionality and obtaining a planning result. The invention has the advantages of optimizing algorithm complexity of the road planning process and improving road planning efficiency.

Description

A kind of path planning that makes up based on chadogram topology road network is determined method
 
Technical field
The present invention relates to a kind of geographic information data processing, computer application field, in particular, a kind of paths planning method that makes up based on chadogram topology road network.
Background technology
At having the actual cities road network that is communicated with character bus stop point, how in polynomial time, to find the solution many bus stops spot net path optimization problem, be that a key of intelligent transportation system studies a question.
At present the majority of network path planning problem generally adopts based on the optimized Algorithm of heuritic approaches such as exact algorithm such as minimum K value method, dynamic programming or genetic algorithm, ant group algorithm and finds the solution.Wherein, Zhan etc. have realized the optimum path search algorithm under the actual traffic road network condition first, but its traditional D-algorithm that adopts carries out circuit search, and is very accurate for the result of calculation of small-scale node, is unacceptable and consume during for needed calculatings of large scale network node.Jagadees etc. propose a kind of node and promote the hierarchy optimization algorithm, can guarantee that algorithm obtains shortest path within a short period of time, but it belongs to a kind of algorithm based on the restriction of road network node scale, only be fit to the fixing network of nodal point number, make that for the uncertainty of real node number this algorithm can't widespread usage.Yanns etc. propose a kind of mixing heuristic algorithm of solution path optimization problem, and the field searching algorithm and the path that have organically combined particle swarm optimization algorithm, multistage field search, self-adaptation greediness, expansion at random reconnect technology.Liu Fei etc. have proposed a kind of the sudden change based on enchancer and have solved networking path optimization problem, because its initial population only has one, can't avoid ubiquitous early stage convergence phenomenon in the genetic algorithm, can not guarantee the diversity of progeny population.Jing Ling etc. proposed based on specific in order, selection, intersection, genetic operator path induce algorithm, and this algorithm is too high for the mass dependence of initial population, if the initialization population is second-rate, then is easy to be absorbed in locally optimal solution.
Therefore, existing technology is existing defective aspect the path planning in the actual road network, needs to improve.
Summary of the invention
In order to overcome the restriction of model solution scale, the slow deficiency of computing velocity of existing actual road network paths planning method, the invention provides the path planning that a kind of path planning model is reasonable, rapidity is good and determine method based on chadogram topology road network structure.
The technical solution adopted for the present invention to solve the technical problems is:
A kind of path planning that makes up based on chadogram topology road network is determined method, may further comprise the steps:
1), obtains the complete road net data in city, the road network full-mesh figure of the original geography information of application adjacency Matrix Method structure expression G, with the road network node abstract be full-mesh figure
Figure 239086DEST_PATH_IMAGE001
In node
Figure 201010606776X100002DEST_PATH_IMAGE002
, and the road network accessibility between the road network node abstract be full-mesh figure
Figure 31593DEST_PATH_IMAGE001
In the limit Connectedness, full-mesh figure
Figure 201010606776X100002DEST_PATH_IMAGE004
, wherein Be nodal set, Expression node number;
Figure 706397DEST_PATH_IMAGE007
Represent the set on limit between each road network node,
Figure 201010606776X100002DEST_PATH_IMAGE008
The bar number on expression limit then has
Figure 404226DEST_PATH_IMAGE009
The limit weight matrix
Figure 201010606776X100002DEST_PATH_IMAGE010
Represent the full figure of UNICOM Limit weights between each node:
Figure 499188DEST_PATH_IMAGE011
Wherein
Figure 201010606776X100002DEST_PATH_IMAGE012
, Presentation graphs
Figure 36797DEST_PATH_IMAGE001
Middle junction label,
Figure 201010606776X100002DEST_PATH_IMAGE014
The expression node
Figure 666492DEST_PATH_IMAGE015
,
Figure 201010606776X100002DEST_PATH_IMAGE016
Between the road network reach distance;
Figure 338258DEST_PATH_IMAGE017
Be the limit weight matrix
Figure 799326DEST_PATH_IMAGE010
Element, the expression link node
Figure 166853DEST_PATH_IMAGE015
,
Figure 346162DEST_PATH_IMAGE016
The limit weights;
2), with road network full-mesh figure GSort out and be divided into y-bend road network topology chadogram;
2.1), with road network full-mesh figure
Figure 558969DEST_PATH_IMAGE001
Abstract to be one be the star-like tree of tie point with abstract tie point, and the node among the full-mesh figure forms the actual node of star-like tree, connects by abstract tie point between the actual node; Full-mesh figure GIn any two nodes
Figure 140123DEST_PATH_IMAGE015
With
Figure 475289DEST_PATH_IMAGE016
Between weights
Figure 79577DEST_PATH_IMAGE017
Be expressed as the abstract limit power sum of two nodes in the abstract star-like tree,
Figure 201010606776X100002DEST_PATH_IMAGE018
, wherein Represent node in the star-like tree
Figure 546383DEST_PATH_IMAGE015
To the abstract limit power between the X,
Figure 201010606776X100002DEST_PATH_IMAGE020
Represent node in the star-like tree
Figure 193396DEST_PATH_IMAGE016
To the abstract limit power between the abstract tie point X;
2.2), obtain any two nodes that characterize in the star-like tree
Figure 81718DEST_PATH_IMAGE015
With
Figure 964223DEST_PATH_IMAGE016
Between syntople in abutting connection with the value
Figure 254390DEST_PATH_IMAGE021
, wherein
Figure 134622DEST_PATH_IMAGE015
,
Figure 510239DEST_PATH_IMAGE016
Figure 201010606776X100002DEST_PATH_IMAGE022
And
Figure 803293DEST_PATH_IMAGE023
Figure 201010606776X100002DEST_PATH_IMAGE024
2.3), concentrate in abutting connection with value result of calculation in each group, select in abutting connection with the minimum node of value to carry out topology reconstruction and to obtain y-bend road network topology chadogram in abutting connection with to keeping each being combined to virtual node inserts in the node set adjacent node as best;
3), according to the adjacency value between the road network node, road network full-mesh figure is carried out classifying and dividing, makes up chadogram topology road network, at line route optimizing problem, employing is carried out dynamic retrogressive method the destination node of circuit optimum path search in the path planning problem is classified, and obtains the minimum branch tree that comprises all destination node;
4), the minimum branch of destination node sets employing branch-and-bound search strategy elimination invalid branch node in all path planning problems for comprising, and reduces the incidence matrix dimension, carries out the path planning analysis on this basis, obtains program results.
Further, in the described step 3), make up chadogram topology road network and adopt above between node,, make up the topological evolvement tree according in abutting connection with the minimum strategy of value in abutting connection with value calculating method
Figure 151229DEST_PATH_IMAGE025
, may further comprise the steps:
3.1.1), the order G={V, E},
Figure 201010606776X100002DEST_PATH_IMAGE026
,
Figure 140045DEST_PATH_IMAGE025
3.1.2), right v i , vj
Figure 201010606776X100002DEST_PATH_IMAGE028
V, calculate v i , v j In abutting connection with the value S Ij
3.1.3), seek v m , v n ,Make v m, v nIn abutting connection with the value S Mn = Min( S Ij ), v m , v n
Figure 980928DEST_PATH_IMAGE028
VWherein, v m , v n Expression road network full-mesh figure GIn any two nodes;
3.1.4), v M-n = vm
Figure 980108DEST_PATH_IMAGE029
v n , V=V-{ v m , v n }+{ v M-n , according to syntople, with father node v M-n , child node v m , child node v n Insert
Figure 949945DEST_PATH_IMAGE025
In;
3.1.5), if VMiddle element number is 1, and algorithm finishes, otherwise changes step 3.1.2).
Further, in the described steps A 3, adopt and dynamically to recall strategy and destination node is classified may further comprise the steps:
3.2.1), obtain destination node
Figure 201010606776X100002DEST_PATH_IMAGE030
,
Figure 300155DEST_PATH_IMAGE031
, obtain node respectively Place layer m, and node Place layer n;
3.2.2), judge
Figure 512459DEST_PATH_IMAGE030
With Whether have same father node, if then obtain all child nodes of common father node and this father node; If not, then obtain the big destination node of place layer, obtain the lineal father node of recalling node as recalling node, with this direct line father node as new destination node, repeating step 3.2.1);
3.2.3), the tree that forms with the common father node of two destination node and all child nodes thereof is as minimum classification tree.
Further, in the described step 4), adopt the fourth elder sister of branch search strategy to comprise following rule to the minimum branches of destination node:
Rule 1, obtain the big destination node of place layer, as the approach node, all destination node form related node set with this approach node with the lineal father node of the big destination node of this place layer or lineal child node; This approach node replacement there is the destination node of lineal relation as new destination node with it;
Rule 2, judge whether new destination node is combined the virtual node that forms by adjacent node, if then with destination node in abutting connection with the minimum non-virtual node replacement of value;
Judge whether virtual node of the father node of new destination node or child node, if then the sibling with its non-virtual node substitutes;
Rule 3, judge whether two destination node are positioned at one deck and have fraternal syntople in the road network topology chadogram, if, then with the arest neighbors binding place in abutting connection with value judgement sequencing; Described arest neighbors contact is meant the be node of distance objective node in abutting connection with the value minimum;
Rule 4, each layer are only selected an approach node, ignore with other branch of layer.
Technical conceive of the present invention is: at first obtain the complete road net data in city, use for reference the thought of chadogram classification in the systems biology then, the syntople evaluation criterion is in abutting connection with the notion of value between introducing road network node, being divided into between road network node adjacency value according to its node syntople classification road network is the road network topology chadogram of sign, simultaneously destination node in the line route optimizing problem is dynamically recalled classification, adopt the branch-and-bound search strategy to search for optimization simultaneously in qualification road network region of search, reduced the searching algorithm time complexity.
Beneficial effect of the present invention mainly shows: the present invention has optimized the algorithm complex of path planning process, has improved the efficient of path planning.
Description of drawings
Fig. 1 is based on the process flow diagram that path planning that chadogram topology road network makes up is determined method.
Fig. 2 is a road network node structural drawing.
Fig. 3 is abstract road network star tree.
Fig. 4 is a node
Figure 201010606776X100002DEST_PATH_IMAGE032
,
Figure 853758DEST_PATH_IMAGE033
Syntople decision model tree.
Fig. 5 selects
Figure 93110DEST_PATH_IMAGE032
,
Figure 382578DEST_PATH_IMAGE033
For in abutting connection with to after the topology reconstruction model tree.
Fig. 6 dynamically recalls the sorting algorithm synoptic diagram.
Fig. 7 is a topological evolvement tree screening synoptic diagram.
Fig. 8 is 30 continent provincial capitals of China topological evolvement tree synoptic diagram.
Fig. 9 is the local dynamic programming synoptic diagram in region of search.
Figure 10 is chadogram path optimization result schematic diagram (32 anchor point).
Embodiment
Embodiment one
With reference to Fig. 1～Figure 10:
A kind of paths planning method that makes up based on chadogram topology road network may further comprise the steps:
1), obtains the complete road net data in city, the road network full-mesh figure of the original geography information of application adjacency Matrix Method structure expression G, with the road network node abstract be full-mesh figure
Figure 707380DEST_PATH_IMAGE001
In node
Figure 14865DEST_PATH_IMAGE002
, and the road network accessibility between the road network node abstract be full-mesh figure In the limit
Figure 640198DEST_PATH_IMAGE003
Connectedness, full-mesh figure
Figure 186717DEST_PATH_IMAGE004
, wherein Be nodal set,
Figure 246257DEST_PATH_IMAGE006
Expression node number;
Figure 151896DEST_PATH_IMAGE007
Represent the set on limit between each road network node, wherein
Figure 182782DEST_PATH_IMAGE008
The bar number on expression limit then has
Figure 894386DEST_PATH_IMAGE009
The limit weight matrix
Figure 697257DEST_PATH_IMAGE010
Represent the full figure of UNICOM Weights between each node:
Figure 201010606776X100002DEST_PATH_IMAGE034
Wherein
Figure 232591DEST_PATH_IMAGE014
The expression node
Figure 419990DEST_PATH_IMAGE015
,
Figure 342947DEST_PATH_IMAGE016
Between the road network reach distance;
Figure 652705DEST_PATH_IMAGE017
Expression limit weight matrix
Figure 661113DEST_PATH_IMAGE010
Element;
2), with road network full-mesh figure GSort out and be divided into y-bend road network topology chadogram;
2.1), with road network full-mesh figure
Figure 655132DEST_PATH_IMAGE001
Abstract to be one be the star-like tree of tie point with abstract tie point, and the node among the full-mesh figure forms the actual node of star-like tree, connects by abstract tie point between the actual node; Full-mesh figure GIn any two nodes
Figure 432595DEST_PATH_IMAGE015
With Between weights
Figure 143379DEST_PATH_IMAGE017
Be expressed as the abstract limit power sum of two nodes in the abstract star-like tree,
Figure 938160DEST_PATH_IMAGE018
, wherein
Figure 570130DEST_PATH_IMAGE019
Represent node in the star-like tree
Figure 159374DEST_PATH_IMAGE015
To the abstract limit power between the X,
Figure 142373DEST_PATH_IMAGE020
Represent node in the star-like tree To the abstract limit power between the abstract tie point X;
Definition: a given abstract road network star tree, the abstract limit of definition road network power summation
Figure 896495DEST_PATH_IMAGE035
For:
(1)
Wherein The expression node
Figure 2303DEST_PATH_IMAGE015
To tie point
Figure 138886DEST_PATH_IMAGE037
Weights, The expression node Arrive
Figure 566509DEST_PATH_IMAGE016
Between weights,
Figure 258522DEST_PATH_IMAGE006
Be road network node number, and have:
Figure 933217DEST_PATH_IMAGE039
,
By formula (1) variant be:
Figure 331968DEST_PATH_IMAGE041
(2)
Also promptly:
Figure 201010606776X100002DEST_PATH_IMAGE042
(3)
Can get thus:
Figure 699496DEST_PATH_IMAGE043
(4)
2.2), obtain any two nodes that characterize in the star-like tree
Figure 610295DEST_PATH_IMAGE015
With
Figure 88681DEST_PATH_IMAGE016
Between syntople in abutting connection with the value
Figure 669835DEST_PATH_IMAGE021
, wherein
Figure 942685DEST_PATH_IMAGE015
,
Figure 609289DEST_PATH_IMAGE016
Figure 688104DEST_PATH_IMAGE022
And
Figure 123764DEST_PATH_IMAGE023
Figure 567515DEST_PATH_IMAGE024
Based on formula (1), the notion of introducing the adjacency value is used to judge node
Figure 721416DEST_PATH_IMAGE015
,
Figure 544534DEST_PATH_IMAGE016
Syntople, wherein
Figure 897018DEST_PATH_IMAGE015
,
Figure 777249DEST_PATH_IMAGE016
And
Figure 511167DEST_PATH_IMAGE023
, definition
Figure 921420DEST_PATH_IMAGE021
The expression node
Figure 706973DEST_PATH_IMAGE015
,
Figure 569887DEST_PATH_IMAGE016
Between in abutting connection with the value, with any 2 points in the network
Figure 794195DEST_PATH_IMAGE015
,
Figure 58954DEST_PATH_IMAGE016
Node is connected with other nodes by two abstract tie point X, Y, as shown in Figure 4, calculates node afterwards
Figure 278059DEST_PATH_IMAGE015
,
Figure 628269DEST_PATH_IMAGE016
Figure 201010606776X100002DEST_PATH_IMAGE044
Value.
In order to calculate the syntople weights of any point-to-point transmission in the road network, introduce to give a definition:
Define figure by Fig. 4
Figure 328371DEST_PATH_IMAGE001
In any 2 points
Figure 447637DEST_PATH_IMAGE015
,
Figure 840572DEST_PATH_IMAGE016
Between in abutting connection with the value
Figure 678078DEST_PATH_IMAGE021
For:
Figure 181872DEST_PATH_IMAGE045
(5)
Define two nodes
Figure 155644DEST_PATH_IMAGE015
With
Figure 710692DEST_PATH_IMAGE016
After the merging, form new node
Figure 201010606776X100002DEST_PATH_IMAGE046
,
Figure 35494DEST_PATH_IMAGE046
With other node limit power be:
Figure 77399DEST_PATH_IMAGE047
(6)
Wherein
Figure 201010606776X100002DEST_PATH_IMAGE048
Figure 108940DEST_PATH_IMAGE022
And
Figure 843678DEST_PATH_IMAGE049
, it is as follows to calculate inference by formula (1) and formula (5):
Figure 201010606776X100002DEST_PATH_IMAGE050
(7)
Proof. will be converted into adjacency Matrix Method in abutting connection with value calculating and represent order Ax=d, wherein
Figure 390197DEST_PATH_IMAGE051
,
Figure 201010606776X100002DEST_PATH_IMAGE052
Be the limit weight matrix between any two nodes, its length is n( n-1)/2, then has ,
Figure 201010606776X100002DEST_PATH_IMAGE054
Be figure GAdjacency matrix represent, wherein:
Figure 322173DEST_PATH_IMAGE055
Will
Figure 201010606776X100002DEST_PATH_IMAGE056
Be converted into
Figure 165496DEST_PATH_IMAGE057
, obtain:
(8)
Wherein
Figure 136994DEST_PATH_IMAGE059
, as shown in Figure 4, ,
Figure 520702DEST_PATH_IMAGE061
For any node with
Figure 592081DEST_PATH_IMAGE032
All processes in the line Road, remove All pass through outward
Figure 127416DEST_PATH_IMAGE062
, then:
Figure 201010606776X100002DEST_PATH_IMAGE064
Other are analogized and obtain matrix
Figure 314815DEST_PATH_IMAGE065
With
Figure 201010606776X100002DEST_PATH_IMAGE066
For:
Figure 201010606776X100002DEST_PATH_IMAGE068
Wherein
Figure 357650DEST_PATH_IMAGE069
,
Figure 201010606776X100002DEST_PATH_IMAGE070
,
Figure 366057DEST_PATH_IMAGE071
,
Figure 201010606776X100002DEST_PATH_IMAGE072
, ,
Figure 201010606776X100002DEST_PATH_IMAGE074
,
Figure 9976DEST_PATH_IMAGE075
Will
Figure 490636DEST_PATH_IMAGE066
In the substitution formula (8), thereby try to achieve:
Figure DEST_PATH_IMAGE076
(9)
Figure 658444DEST_PATH_IMAGE077
(10)
Figure DEST_PATH_IMAGE078
(11)
Figure 405556DEST_PATH_IMAGE079
(12)
Wherein
Figure DEST_PATH_IMAGE080
,
Figure 37525DEST_PATH_IMAGE081
,
Figure DEST_PATH_IMAGE082
,
Figure 564453DEST_PATH_IMAGE083
, following formula and formula (5) simultaneous can be eliminated known variables ,
Figure 880345DEST_PATH_IMAGE020
,
Figure DEST_PATH_IMAGE084
,
Figure 366821DEST_PATH_IMAGE085
, try to achieve
Figure 389616DEST_PATH_IMAGE021
Final calculating formula as follows:
Card is finished.
2.3), concentrate in abutting connection with value result of calculation in each group, select in abutting connection with the minimum node of value to as best in abutting connection with to keeping, each is combined in the virtual node insertion node set adjacent node, and this adjacent node of deletion is right in nodal set, carries out topology reconstruction and obtains y-bend road network topology chadogram;
As shown in Figure 5, below prove for topology reconstruction rule and legitimacy thereof:
Topology reconstruction rule: supposition
Figure 465336DEST_PATH_IMAGE015
With
Figure 71898DEST_PATH_IMAGE016
For adjacent node right, then with node
Figure 330841DEST_PATH_IMAGE015
With
Figure 757274DEST_PATH_IMAGE016
Form a new node, be defined as virtual node
Figure 697549DEST_PATH_IMAGE046
, show as
Figure DEST_PATH_IMAGE086
Middle deletion node
Figure 96300DEST_PATH_IMAGE015
,
Figure 260565DEST_PATH_IMAGE016
, insert new node , make up the new road network of principle construction according to abstract graph afterwards
Figure 921189DEST_PATH_IMAGE087
Legitimacy proves: with node
Figure 236764DEST_PATH_IMAGE032
,
Figure 775193DEST_PATH_IMAGE033
Be example, suppose
Figure 176218DEST_PATH_IMAGE032
,
Figure 458295DEST_PATH_IMAGE033
For adjacent node right, as shown in Figure 5, the connected graph behind the topology reconstruction
Figure 893956DEST_PATH_IMAGE087
Should satisfy formula (1), promptly need prove:
Figure DEST_PATH_IMAGE088
(13)
Proof:
(1) for right formula in the formula (13), as can be known by formula (9):
Simultaneous
Figure DEST_PATH_IMAGE090
, . the abbreviation following formula gets:
Figure 246549DEST_PATH_IMAGE091
Then can obtain:
Figure DEST_PATH_IMAGE092
(2) for levoform in the formula (13), by formula (6), as can be known:
Figure 474399DEST_PATH_IMAGE093
Wherein D 13= D 1 A + L AX + L 3 X , D 23= D 2 A + L AX + L 3 X , then the following formula type variable is:
Figure DEST_PATH_IMAGE094
Also promptly:
Figure 89051DEST_PATH_IMAGE095
To sum up, levoform=right formula, then
Card is finished.
Above-mentioned proof topology constructing again satisfies formula (1) requirement, thus seek each to adjacent node after, it merged into virtual node and insert in the node set, carry out topology reconstruction;
3), according to the adjacency value between the road network node, road network full-mesh figure is carried out classifying and dividing, makes up chadogram topology road network, at line route optimizing problem, employing is carried out dynamic retrogressive method the destination node of circuit optimum path search in the path planning problem is classified, and obtains the minimum branch tree that comprises all destination node;
4), the minimum branch of destination node sets employing branch-and-bound search strategy elimination invalid branch node in all path planning problems for comprising, and reduces the incidence matrix dimension, carries out the path planning analysis on this basis, obtains program results.
In the described step 3), make up chadogram topology road network and adopt above between node,, make up the topological evolvement tree according in abutting connection with the minimum strategy of value in abutting connection with value calculating method
Figure 88548DEST_PATH_IMAGE025
, may further comprise the steps:
3.1.1), the order G={V, E},
Figure DEST_PATH_IMAGE096
,
Figure 162116DEST_PATH_IMAGE025
3.1.2), right v i , vj
Figure 138479DEST_PATH_IMAGE028
V(G), calculate v i , v j In abutting connection with the value S Ij
3.1.3), seek v m , v n ,Make v m, v nIn abutting connection with the value S Mn = Min( S Ij ), v m , vn
Figure 300470DEST_PATH_IMAGE028
V(G)Wherein, v m, v nAny two nodes among the expression road network full-mesh figure G;
3.1.4), v M-n = vm
Figure 565230DEST_PATH_IMAGE029
v n , V=V-{ v m , v n }+{ v M-n , according to syntople, with father node v M-n , child node v m , child node v n Insert
Figure 787264DEST_PATH_IMAGE025
In; Described syntople is according to judging in abutting connection with value, and is tight more in abutting connection with the more little syntople of value, is meant that according to syntople two nodes are child node, and the virtual node of its formation is a such set membership of father node;
3.1.5), if VMiddle element number is 1, and algorithm finishes, otherwise changes step 3.2).
In the described steps A 3, adopt and dynamically to recall strategy and destination node is classified may further comprise the steps:
3.2.1), obtain destination node ,
Figure 837576DEST_PATH_IMAGE031
, obtain node respectively
Figure 953912DEST_PATH_IMAGE030
Place layer m, and node
Figure 409164DEST_PATH_IMAGE031
Place layer n;
3.2.2), judge
Figure 246670DEST_PATH_IMAGE030
With
Figure 750464DEST_PATH_IMAGE031
Whether have same father node, if then obtain all child nodes of common father node and this father node; If not, then obtain the big destination node of place layer, obtain the lineal father node of recalling node as recalling node, with this direct line father node as new destination node, repeating step 3.2.1);
3.2.3), the tree that forms with the common father node of two destination node and all child nodes thereof is as minimum classification tree.
In the described step 4), adopt the fourth elder sister of branch search strategy to comprise following rule to the minimum branches of destination node:
Rule 1, obtain the big destination node of place layer, as the approach node, all destination node form related node set with this approach node with the lineal father node of the big destination node of this place layer or lineal child node; This approach node replacement there is the destination node of lineal relation as new destination node with it;
Rule 2, judge whether new destination node is combined the virtual node that forms by adjacent node, if then with destination node in abutting connection with the minimum non-virtual node replacement of value;
Judge whether virtual node of the father node of new destination node or child node, if then the sibling with its non-virtual node substitutes;
Rule 3, judge whether two destination node are positioned at one deck and have fraternal syntople in the road network topology chadogram, if, then with the arest neighbors binding place in abutting connection with value judgement sequencing; Described arest neighbors contact is meant the be node of distance objective node in abutting connection with the value minimum;
Rule 4, each layer are only selected an approach node, ignore with other branch of layer.
Technical conceive of the present invention is: at first obtain the complete road net data in city, use for reference the thought of chadogram classification in the systems biology then, the syntople evaluation criterion is in abutting connection with the notion of value between introducing road network node, being divided into between road network node adjacency value according to its node syntople classification road network is the road network topology chadogram of sign, simultaneously destination node in the line route optimizing problem is dynamically recalled classification, adopt the branch-and-bound search strategy to search for optimization simultaneously in qualification road network region of search, reduced the searching algorithm time complexity.
Embodiment two
In conjunction with the complete road network of actual cities, further specify the present invention:
A kind of path planning that makes up based on chadogram topology road network is determined method, as shown in Figure 1, wherein comprises following steps:
A1, obtain the complete road net data in city, make up road network full-mesh figure
Figure 724236DEST_PATH_IMAGE097
, wherein
Figure 288073DEST_PATH_IMAGE005
Be the road network nodal set,
Figure 347296DEST_PATH_IMAGE006
Expression node number.
Figure 654780DEST_PATH_IMAGE007
Represent the set on limit between each road network node, wherein
Figure 810955DEST_PATH_IMAGE008
The bar number on expression limit, the limit weight matrix
Figure 545693DEST_PATH_IMAGE010
Represent the full figure of UNICOM
Figure 95141DEST_PATH_IMAGE001
Weights between each node
Figure DEST_PATH_IMAGE098
,
Figure 878421DEST_PATH_IMAGE014
Be expressed as node in the road network
Figure 889102DEST_PATH_IMAGE002
,
Figure 794741DEST_PATH_IMAGE016
Between the road network reach distance; A2, with road network full-mesh figure
Figure 828556DEST_PATH_IMAGE001
Being divided into adjacency value between the road network node according to its node syntople classification is the y-bend road network topology chadogram of sign; A3, according to chadogram topology road network, make up line route optimizing problem, dynamically recall classification for destination node in the problem, obtain the minimum branch tree that comprises all destination node; A4, adopt the branch-and-bound search strategy to eliminate the invalid branch node, further reduce the incidence matrix dimension, on this basis, carry out the path planning analysis, obtain program results faster for the minimum branch tree that comprises all path planning destination node.
Described method, wherein, in steps A 1, obtain the complete road net data in city, should comprise between the longitude and latitude, node of road network node geography information such as road network reach distance in the road net data, as adopting the china administration central data file res1_4m of national fundamental geographic information system (NFGIS) 1:400 ten thousand ratios, this document (.shp, the graphical format of GIS) comprises 30 continent provincial capital information, can download from http://nfgis.nsd-i.gove.cn.
Described method wherein, in steps A 1, at the complete road net data in city, makes up road network full-mesh figure
Figure 477844DEST_PATH_IMAGE097
, wherein
Figure 546294DEST_PATH_IMAGE005
Be the road network nodal set,
Figure 622834DEST_PATH_IMAGE006
Expression node number.
Figure 940683DEST_PATH_IMAGE007
Represent the set on limit between each road network node, wherein
Figure 390731DEST_PATH_IMAGE008
The bar number on expression limit, the limit weight matrix
Figure 313688DEST_PATH_IMAGE010
Represent the full figure of UNICOM
Figure 561130DEST_PATH_IMAGE001
Weights between each node
Figure 303958DEST_PATH_IMAGE098
,
Figure 295048DEST_PATH_IMAGE014
Be expressed as node in the road network
Figure 134828DEST_PATH_IMAGE002
,
Figure 553171DEST_PATH_IMAGE016
Between the road network reach distance.
Described method, wherein, in steps A 2, at road network full-mesh figure
Figure 48874DEST_PATH_IMAGE001
, calculate road network full-mesh figure
Figure 578075DEST_PATH_IMAGE001
In between any two nodes in abutting connection with value.At first according to road network full-mesh figure
Figure 490273DEST_PATH_IMAGE001
, the adjacency of calculating wherein any two nodes is worth, and forms current road network full-mesh figure
Figure 79517DEST_PATH_IMAGE001
Node in abutting connection with value collection, concentrate in abutting connection with value result of calculation in each group, select in abutting connection with the minimum node of value to as best in abutting connection with to keeping, the applied topology reconfiguration rule is reconstructed road network afterwards,
Described method wherein, in steps A 2, at road network topology reconstruct, adopts following rule: supposition
Figure 796937DEST_PATH_IMAGE015
With
Figure 192147DEST_PATH_IMAGE016
For adjacent node right, then with node
Figure 944202DEST_PATH_IMAGE015
With
Figure 704347DEST_PATH_IMAGE016
Form a new node, be defined as virtual node
Figure 909064DEST_PATH_IMAGE046
, show as
Figure 45647DEST_PATH_IMAGE086
Middle deletion node
Figure 652209DEST_PATH_IMAGE015
,
Figure 580326DEST_PATH_IMAGE016
, insert new node , make up the new road network of principle construction according to abstract graph afterwards
Figure 274930DEST_PATH_IMAGE087
Described method, wherein, in steps A 3, according to result of calculation in the steps A 2, make up the road network topology chadogram, as the china administration central data file res1_4m at national fundamental geographic information system (NFGIS) 1:400 ten thousand ratios, this document (.shp, the graphical format of GIS) comprise 30 continent provincial capital geography information, adopt following algorithm to realize that the road network topology chadogram makes up (making up result such as Fig. 8):
1. order G={V, E},
Figure 735998DEST_PATH_IMAGE026
, the initialization chadogram
Figure 588679DEST_PATH_IMAGE025
2. right
Figure 770917DEST_PATH_IMAGE027
v i , vJ V(G), calculate v i , v j In abutting connection with the value S Ij
3. seek v m , v n ,Make S Mn = Min( S Ij ), v m , vn
Figure 564878DEST_PATH_IMAGE028
V(G)
4. v M-n = vm
Figure 165623DEST_PATH_IMAGE029
v n , V=V-{ v m , v n }+{ v M-n , according to syntople, will v M-n (father node), v m (child node), v n (child node) inserts
Figure 566649DEST_PATH_IMAGE025
In
If VMiddle element number is 1, and algorithm finishes, otherwise changes step 2.
Described method wherein, in steps A 3, at the road network topology chadogram, adopts dynamic retrogressive method to obtain to comprise the minimum branch tree of all path planning destination node to comprise following steps, obtains start node And destination node , traversal road network topology chadogram
Figure 728137DEST_PATH_IMAGE025
, judge
Figure 616458DEST_PATH_IMAGE030
,
Figure 433717DEST_PATH_IMAGE099
Figure 786201DEST_PATH_IMAGE025
In the position, suppose
Figure 666432DEST_PATH_IMAGE030
,
Figure 42050DEST_PATH_IMAGE031
Be in respectively
Figure 665930DEST_PATH_IMAGE025
m, nLayer is recalled respectively
Figure 810603DEST_PATH_IMAGE030
,
Figure 861736DEST_PATH_IMAGE031
Father node, when the two dates back to same father node, stop, keep this node and with inferior division tree, as comprising the minimum classification tree of destination node, algorithm flow as shown in Figure 6.
Described method wherein, in steps A 4, also comprises following steps, comprises the minimum branch tree of all path planning destination node, adopts branch-bound algorithm that planning process is optimized, and is example with Fig. 7, and definition rule is as follows:
1. according to the adjacency of destination node, first-selected lineal father node or lineal child node, among Fig. 7 from
Figure 724649DEST_PATH_IMAGE030
Set out, then at first select As the approach node, this moment, related node set was
Figure DEST_PATH_IMAGE100
2. if the father node or the child node of destination node is virtual node, then substitute with its sibling, among Fig. 7 from Set out, its father node is
Figure 99065DEST_PATH_IMAGE101
, then with node
Figure DEST_PATH_IMAGE102
Substitute
Figure 386958DEST_PATH_IMAGE101
3. if two destination node are positioned at same level and have fraternal syntople, then to judge sequencing, in Fig. 7 with the adjacency value of arest neighbors binding place
Figure 352640DEST_PATH_IMAGE030
,
Figure 409589DEST_PATH_IMAGE033
,
Figure 802524DEST_PATH_IMAGE103
Be the stop website, have two kinds of stop orders this moment, promptly S-2-3 or S-3-2 arrive the big or small in abutting connection with value of some S according to putting 2,3, judging point 2 and point 3 those nearer apart from S, near stops earlier, back stop far away, as 2 nearer apart from S, then stop is S-2-3 in proper order, otherwise then is S-3-2; Therefore,
Figure 371522DEST_PATH_IMAGE030
,
Figure 875315DEST_PATH_IMAGE033
Be positioned at same one deck, then judge
Figure DEST_PATH_IMAGE104
,
Figure 865399DEST_PATH_IMAGE105
Size decides the stop order.
4. each layer is only selected an approach node, ignores with other branch of layer, as selecting
Figure 429236DEST_PATH_IMAGE033
As the approach node, then ignore And branch tree.
Described method, wherein, in steps A 4, also comprise following steps, to comprise all road networks of stopping website and be reconstructed into road network topology chadogram with syntople performance feature, use dynamic retrogressive method and obtain the minimum branch tree that comprises required stop website, adopt the branch-and-bound optimisation strategy stopping Website Hosting
Figure DEST_PATH_IMAGE106
Carry out topological sorting, design path planning algorithm step is as follows on this basis:
1. road network topology reconstruct is carried out topology reconstruction with whole road network according to syntople, and finally forming with the syntople is the road network topology chadogram of performance characteristic Tree
2. according to stopping Website Hosting V=( v 1 , v 2 ... v n ), adopt and dynamically recall classification policy, TreeThe minimum branch of middle searching tree B- Tree, satisfy condition:
Figure 736556DEST_PATH_IMAGE107
For comprise ( v 1 , v 2 ... v n ) minimum branch tree B- Tree, follow the branch-and-bound optimisation strategy, obtain according to syntople and judge the order of cruising of respectively stopping node visit priority
Figure DEST_PATH_IMAGE108
And output.
4. the sequence applied dynamic programming strategy that simultaneously step 3 is obtained carries out part adjustment, be about to ( v 1 , v 2 ... v n ) in be positioned at B- TreeNode and other nodes of same branch tree are separated, and node applied dynamic programming in the limited field is accurately found the solution, and merge with the relation of adjoining each other with other nodes afterwards, obtain optimum solution, as shown in Figure 9.
Fig. 9 has provided the situation of the local dynamic programming in region of search, wherein B-Tree '
Figure 830414DEST_PATH_IMAGE109
B- Tree, v 2 , v 3 , v 4 For B-Tree 'The stop node that is comprised will B-Tree ' B- TreeIn separate, to ( v 2 , v 3 ,, v 4 ) carry out dynamic programming and find the solution the local optimum route
Figure DEST_PATH_IMAGE110
, be inserted into according to syntople afterwards
Figure 502835DEST_PATH_IMAGE108
In, obtain through the route of cruising after the local optimum, wherein
Figure 49354DEST_PATH_IMAGE111
Be
Figure DEST_PATH_IMAGE112
A rule displacement.
The path planning algorithm average time complexity that makes up based on the road network topology chadogram among the present invention is , wherein nThe number of stopping website in the expression path planning problem.
Path optimization's algorithm according to the road network topology chadogram, consider actual road network accessibility, 32 provincial capitals in China's Mainland picked at random is stopped website carry out the optimum path search algorithm simulating, with stop website combination Beijing, Shijiazhuang, Taiyuan, Shenyang, Changchun, Xi'an, Chengdu is embodiment, and the path planning algorithm process that makes up based on the road network topology chadogram is as follows:
Step1: obtain the complete road net data of China's Mainland provincial capital,, make up the road network topology chadogram, as shown in Figure 8 according to the relation of adjoining each other between each city.
Step2 :Use and dynamically recall Beijing in the strategy judgement road network topology chadogram, Shijiazhuang, Taiyuan, Shenyang, Changchun, Xi'an, the minimum branch in place, Chengdu tree.
Step3 :Invalid node during the minimum branch that adopts the elimination of branch-and-bound strategy to comprise Beijing, Shijiazhuang, Taiyuan, Shenyang, Changchun, Xi'an, Chengdu sets is used to reduce path planning problem incidence matrix dimension.
Step4 :The design path planning algorithm, and obtain the path planning scheme that comprises Beijing, Shijiazhuang, Taiyuan, Shenyang, Changchun, Xi'an, Chengdu destination node, adopting the topological sorting algorithm solving result is sequence: Changchun → Shenyang → Beijing → Taiyuan → Shijiazhuang → Xi'an → Chengdu, desired value is 35.0420 (1:400 ten thousand engineer's scales), as shown in figure 10.
What more than set forth is the good optimization effect that a embodiment that the present invention provides shows, obviously the present invention not only is fit to the foregoing description, can do many variations to it under the prerequisite of the related content of flesh and blood of the present invention and is implemented not departing from essence spirit of the present invention and do not exceed.

Claims (4)

1. a path planning that makes up based on chadogram topology road network is determined method, may further comprise the steps:
1), obtains the complete road net data in city, the road network full-mesh figure of the original geography information of application adjacency Matrix Method structure expression G, with the road network node abstract be full-mesh figure
Figure DEST_PATH_IMAGE002
In node
Figure DEST_PATH_IMAGE004
, and the road network accessibility between the road network node abstract be full-mesh figure
Figure 171643DEST_PATH_IMAGE002
In the limit
Figure DEST_PATH_IMAGE006
Connectedness, full-mesh figure , wherein
Figure DEST_PATH_IMAGE010
Be nodal set, Expression node number;
Figure DEST_PATH_IMAGE014
Represent the set on limit between each road network node,
Figure DEST_PATH_IMAGE016
The bar number on expression limit then has
Figure DEST_PATH_IMAGE018
The limit weight matrix
Figure DEST_PATH_IMAGE020
Represent the full figure of UNICOM
Figure 108725DEST_PATH_IMAGE002
Limit weights between each node:
Wherein
Figure DEST_PATH_IMAGE024
, Presentation graphs
Figure 581032DEST_PATH_IMAGE002
Middle junction label,
Figure DEST_PATH_IMAGE028
The expression node
Figure DEST_PATH_IMAGE030
,
Figure DEST_PATH_IMAGE032
Between the road network reach distance;
Figure DEST_PATH_IMAGE034
Be the limit weight matrix Element, the expression link node
Figure 764944DEST_PATH_IMAGE030
,
Figure 321696DEST_PATH_IMAGE032
The limit weights;
2), with road network full-mesh figure GSort out and be divided into y-bend road network topology chadogram;
2.1), with road network full-mesh figure GAbstract to be one be the star-like tree of tie point with abstract tie point, and the node among the full-mesh figure forms the actual node of star-like tree, connects by abstract tie point between the actual node; Full-mesh figure GIn any two nodes
Figure 103970DEST_PATH_IMAGE030
With
Figure 838707DEST_PATH_IMAGE032
Between weights
Figure 634494DEST_PATH_IMAGE034
Be expressed as the abstract limit power sum of two nodes in the abstract star-like tree,
Figure DEST_PATH_IMAGE036
, wherein
Figure DEST_PATH_IMAGE038
Represent node in the star-like tree
Figure 251330DEST_PATH_IMAGE030
To the abstract limit power between the X,
Figure DEST_PATH_IMAGE040
Represent node in the star-like tree
Figure 12744DEST_PATH_IMAGE032
To the abstract limit power between the abstract tie point X, ,
Figure 824635DEST_PATH_IMAGE026
Presentation graphs Middle junction label;
2.2), obtain any two nodes that characterize in the star-like tree With
Figure 242082DEST_PATH_IMAGE032
Between syntople in abutting connection with the value
Figure DEST_PATH_IMAGE042
, wherein
Figure 622247DEST_PATH_IMAGE030
,
Figure 763641DEST_PATH_IMAGE032
Figure DEST_PATH_IMAGE044
And
Figure DEST_PATH_IMAGE046
,
Figure DEST_PATH_IMAGE048
The expression node
Figure 683668DEST_PATH_IMAGE004
With node
Figure DEST_PATH_IMAGE050
Between the limit weights,
Figure DEST_PATH_IMAGE052
The expression node
Figure 744159DEST_PATH_IMAGE032
With node
Figure 172473DEST_PATH_IMAGE050
Between the limit weights,
Figure DEST_PATH_IMAGE054
The expression node
Figure 38929DEST_PATH_IMAGE050
With node
Figure DEST_PATH_IMAGE056
Between the limit weights;
Figure DEST_PATH_IMAGE058
2.3), concentrate in abutting connection with value result of calculation in each group, select in abutting connection with the minimum node of value to carry out topology reconstruction and to obtain y-bend road network topology chadogram in abutting connection with to keeping each being combined to virtual node inserts in the node set adjacent node as best;
3), according to the adjacency value between the road network node, road network full-mesh figure is carried out classifying and dividing, makes up chadogram topology road network, at line route optimizing problem, employing is carried out dynamic retrogressive method the destination node of circuit optimum path search in the path planning problem is classified, and obtains the minimum branch tree that comprises all destination node;
4), the minimum branch of destination node sets employing branch-and-bound search strategy elimination invalid branch node in all path planning problems for comprising, and reduces the incidence matrix dimension, carries out the path planning analysis on this basis, obtains program results.
2. the path planning that makes up based on chadogram topology road network as claimed in claim 1 is determined method, it is characterized in that: in the described step 3), make up chadogram topology road network and adopt above between node,, make up the topological evolvement tree according in abutting connection with the minimum strategy of value in abutting connection with value calculating method
Figure DEST_PATH_IMAGE060
, may further comprise the steps:
3.1.1), the order G={V, E}, the limit weight matrix
Figure DEST_PATH_IMAGE062
, initial chadogram
Figure 187364DEST_PATH_IMAGE060
3.1.2), select any node v i , v j
Figure DEST_PATH_IMAGE064
V, right
Figure DEST_PATH_IMAGE066
v i , v, calculate v i , v j In abutting connection with the value S Ij
3.1.3), seek node v m , v n ,Make v m , v n In abutting connection with the value S Mn = Min( S Ij ), v m , v n V(G)Wherein, v m , v n Any two nodes among the expression road network full-mesh figure G;
3.1.4), with step 3.1.3) in obtain v m , v n Merge into new node v M-n , promptly v M-n = vm
Figure DEST_PATH_IMAGE068
v n , V=V-{ v m , v n }+{ v M-n , according to syntople, with father node v M-n , child node v m , child node v n Insert
Figure 350678DEST_PATH_IMAGE060
In;
3.1.5), if VMiddle element number is 1, and algorithm finishes, otherwise changes step 3.1.2).
3. the path planning that makes up based on chadogram topology road network as claimed in claim 2 is determined method, it is characterized in that: in the described steps A 3, adopt and dynamically recall strategy and destination node is classified may further comprise the steps:
3.2.1), obtain destination node
Figure DEST_PATH_IMAGE070
,
Figure DEST_PATH_IMAGE072
, obtain node respectively
Figure 651119DEST_PATH_IMAGE070
Be positioned at the topological evolvement tree
Figure 797936DEST_PATH_IMAGE060
Place level label, and node
Figure 387180DEST_PATH_IMAGE072
Be positioned at the topological evolvement tree
Figure 793016DEST_PATH_IMAGE060
Place level label;
3.2.2), judge
Figure 375176DEST_PATH_IMAGE070
With
Figure DEST_PATH_IMAGE074
Whether have same father node, if then obtain all child nodes of common father node and this father node; If not, then obtain the big destination node of place layer, obtain the lineal father node of recalling node as recalling node, with this direct line father node as new destination node, repeating step 3.2.1);
3.2.3), the tree that forms with the common father node of two destination node and all child nodes thereof is as minimum classification tree.
4. the path planning that makes up based on chadogram topology road network as claimed in claim 3 is determined method, it is characterized in that: in the described step 4), adopt the branch-and-bound search strategy to comprise following rule to the minimum branches of destination node:
Rule 1, obtain the big destination node of place layer, as the approach node, all destination node form related node set with this approach node with the lineal father node of the big destination node of this place layer or lineal child node; This approach node replacement there is the destination node of lineal relation as new destination node with it;
Rule 2, judge whether new destination node is combined the virtual node that forms by adjacent node, if then with destination node in abutting connection with the minimum non-virtual node replacement of value;
Judge whether virtual node of the father node of new destination node or child node, if then the sibling with its non-virtual node substitutes;
Rule 3, judge whether two destination node are positioned at one deck and have fraternal syntople in the road network topology chadogram, if, then with the arest neighbors binding place in abutting connection with value judgement sequencing; Described arest neighbors contact is meant the be node of distance objective node in abutting connection with the value minimum;
Rule 4, each layer are only selected an approach node, ignore with other branch of layer.
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